How to filter the age of Telegram users? A practical guide for operators

paying more and more attention toUnder the trend of "refined user operations", Telegram, as a decentralized and highly interactive social platform, also needs to start layering user portraits. Gender can be used as a base dimension, whileageIt more directly affects a user’s interest preferences, language style, decision-making rhythm and conversion path.

especially inIn Telegram’s private chat marketing, community management, and guided Bot design, the strategy execution varies greatly among different age groups. So, here comes the question:How to create a page without explicit age fieldIn the Telegram platform, how to determine the age structure of accounts in batches?

age tag inKey role in Telegram’s operations

In most social platforms, age determines a user’s communication style, content needs, and conversion sensitivity. put onIn the operation of Telegram, the impact is particularly significant:

l18-24 years old group: The pursuit of fast excitement, the content style is entertainment-oriented, suitable for fission new recruits, red envelope guidance, and trendy projects.

l25-35 years old group: Have certain rational judgment ability and payment ability, and are the core objects of most conversion behaviors.

lUsers over 36 years old: Preference for stable products, strong value orientation, more sensitive to project background and service capabilities, suitable for in-depth private chat conversion.

If you can know the approximate age of the other person in advance, then start fromNickname design,Message content,Rhythm of speecharriveProduct guidance, can be targeted.

How to determine the age group of a Telegram account?

AlthoughTelegram does not require real names and does not display birth year, but it can construct age tags from multi-dimensional signs:

1. User nickname and username analysis

Many users’ usernames will includeYear of birth such as "1990", "88", "02", etc., or the nickname directly states "Jack_90" or "Lily2001".

This kind of information can be extracted in batches through regular matching and text recognition to determine the possible year of birth, and then calculate the age group.

In addition, the nickname appearsLabeled morphemes such as "little baby mom", "aunt" and "post-90s youth" can also infer the age tendency of users.

2. Age characteristic identification of content behavior

Behavioral data is a powerful source of signals. For example:

lYoung users are more likely to interact frequently, use stickers intensively, participate in sweepstakes, and join two-dimensional or topical channels.

lAdult users prefer financial channels and project toolsBot, long message reading, proactive private chat with customer service, etc.

do these actions"Cluster modeling", combined with sample database experience, can assist in inferring the age group of the user.

3. Avatar style and language mode

lThe avatars of young users prefer selfies, beauty, and anime images, and their language is mixed with trendy vocabulary.

lThe avatars of mature users tend to be business avatars, real photos, and the language is more standardized.

Assisted reasoning through image recognition and language models can also make up for the blind spots caused by the lack of direct fields.

accomplishThe practical way to filter age on Telegram

If operators want to complete age screening before using accounts on a large scale or reaching target users, they can rely on the following steps:

1.Prepare a list of account information: IncludingTelegram ID, nickname, username and other fields

2.Upload to analysis system: Support batch field identification and modeling analysis

3.Set label output logic: System identificationSensitive fields such as "90" and "2000" and their semantic tendencies

4.Output account file containing age tags,For example"25-35 years old, high confidence"

5.Export grouped by age group: To adapt to subsequent mass sending, community distribution, and private chat conversion paths

The most important thing in the implementation of this process is the platform's data recognition capability and dimensional modeling accuracy.

Why is it recommended to use"Digital Planet" conducts age screening on Telegram?

Many users have already chosenDigital Planet Platformto batch processAge stratification task for Telegram accounts.

The advantages of the platform are reflected in:

lHigh-precision nickname age field extraction capability: Combining global language habits and birth year recognition models to identify age clues implicit in nicknames

lBehavioral models assist judgment: Comprehensive judgment of age group trends through user interaction trajectories and behavioral preferences.

lAvatar recognition integration: Supports age recognition based on avatar style, further improving overall accuracy.

lLabeled export: Automatically marked asCommonly used age group formats such as "18-24 years old/25-35 years old/over 36 years old" are convenient for subsequent use.

lStrong linkage: Can be used in combination with gender recognition, activity filtering, account status detection and other modules to achieve integrated strategic grouping

Currently, users of Digital Planet have passed age screening in multiple overseas projects:

lSwitching the operational speaking style (such as being more lively for young people)

lImproved advertising accuracy (targetedConversion core group aged 25-35)

lCommunity strategy level (create different styles of communities based on age groups)

lBot interactive menu personalization (triggering different logic based on age group)

If you are facing the problem of a large number of accounts that cannot be stratified, and it is difficult to increase conversion efficiency through private messages, you might as well try using Digital Planet.Telegram age stratified identification, making the communication between you and your customers warmer and more accurate.

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